{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T20:49:35Z","timestamp":1760647775988,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031265037"},{"type":"electronic","value":"9783031265044"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-26504-4_44","type":"book-chapter","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T08:02:59Z","timestamp":1677052979000},"page":"531-536","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Variable Neighborhood Descent for\u00a0Software Quality Optimization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5956-9977","authenticated-orcid":false,"given":"Javier","family":"Yuste","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6247-5269","authenticated-orcid":false,"given":"Eduardo G.","family":"Pardo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4532-3124","authenticated-orcid":false,"given":"Abraham","family":"Duarte","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,23]]},"reference":[{"issue":"2","key":"44_CR1","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/TKDE.2007.190689","volume":"20","author":"U Brandes","year":"2007","unstructured":"Brandes, U., et al.: On modularity clustering. IEEE Trans. Knowl. Data Eng. 20(2), 172\u2013188 (2007)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"doi-asserted-by":"crossref","unstructured":"Cavero, S., Pardo, E.G., Duarte, A.: A general variable neighborhood search for the cyclic antibandwidth problem. Comput. Optim. Appl. 81, 657\u2013687 (2022)","key":"44_CR2","DOI":"10.1007\/s10589-021-00334-y"},{"doi-asserted-by":"crossref","unstructured":"Chen, C., Alfayez, R., Srisopha, K., Boehm, B., Shi, L.: Why is it important to measure maintainability and what are the best ways to do it? In: 2017 IEEE\/ACM 39th International Conference on Software Engineering Companion (ICSE-C), pp. 377\u2013378. IEEE (2017)","key":"44_CR3","DOI":"10.1109\/ICSE-C.2017.75"},{"unstructured":"International Organization for Standardization: ISO\/IEC\/IEEE 24765:2017 Systems and software engineering - Vocabulary (2017)","key":"44_CR4"},{"key":"44_CR5","first-page":"43","volume":"3","author":"M L\u00f3pez-Ib\u00e1\u00f1ez","year":"2016","unstructured":"L\u00f3pez-Ib\u00e1\u00f1ez, M., Dubois-Lacoste, J., C\u00e1ceres, L.P., Birattari, M., St\u00fctzle, T.: The irace package: iterated racing for automatic algorithm configuration. Oper. Res. Perspect. 3, 43\u201358 (2016)","journal-title":"Oper. Res. Perspect."},{"unstructured":"Mancoridis, S., Mitchell, B.S., Rorres, C., Chen, Y.F., Gansner, E.R.: Using automatic clustering to produce high-level system organizations of source code. In: 6th International Workshop on Program Comprehension (IWPC 1998), pp. 45\u201352. IEEE (1998)","key":"44_CR6"},{"doi-asserted-by":"publisher","unstructured":"Mart\u00edn, R., Cavero, S.: MORK: Metaheuristic Optimization framewoRK. https:\/\/doi.org\/10.5281\/zenodo.6241738","key":"44_CR7","DOI":"10.5281\/zenodo.6241738"},{"issue":"11","key":"44_CR8","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.1016\/S0305-0548(97)00031-2","volume":"24","author":"N Mladenovi\u0107","year":"1997","unstructured":"Mladenovi\u0107, N., Hansen, P.: Variable neighborhood search. Comput. Oper. Res. 24(11), 1097\u20131100 (1997)","journal-title":"Comput. Oper. Res."},{"key":"44_CR9","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.cor.2017.10.004","volume":"91","author":"MC Mon\u00e7ores","year":"2018","unstructured":"Mon\u00e7ores, M.C., Alvim, A.C.F., Barros, M.O.: Large neighborhood search applied to the software module clustering problem. Comput. Oper. Res. 91, 92\u2013111 (2018)","journal-title":"Comput. Oper. Res."},{"issue":"5","key":"44_CR10","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1007\/s10796-019-09906-0","volume":"22","author":"L Mu","year":"2020","unstructured":"Mu, L., Sugumaran, V., Wang, F.: A hybrid genetic algorithm for software architecture re-modularization. Inf. Syst. Front. 22(5), 1133\u20131161 (2020)","journal-title":"Inf. Syst. Front."},{"key":"44_CR11","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1016\/j.infsof.2014.07.015","volume":"57","author":"M de Oliveira Barros","year":"2015","unstructured":"de Oliveira Barros, M., de Almeida Farzat, F., Travassos, G.H.: Learning from optimization: a case study with apache ant. Inf. Softw. Technol. 57, 684\u2013704 (2015)","journal-title":"Inf. Softw. Technol."},{"issue":"2","key":"44_CR12","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1109\/TSE.2010.26","volume":"37","author":"K Praditwong","year":"2010","unstructured":"Praditwong, K., Harman, M., Yao, X.: Software module clustering as a multi-objective search problem. IEEE Trans. Softw. Eng. 37(2), 264\u2013282 (2010)","journal-title":"IEEE Trans. Softw. Eng."},{"key":"44_CR13","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1016\/j.jss.2018.12.015","volume":"149","author":"A Ramirez","year":"2019","unstructured":"Ramirez, A., Romero, J.R., Ventura, S.: A survey of many-objective optimisation in search-based software engineering. J. Syst. Softw. 149, 382\u2013395 (2019)","journal-title":"J. Syst. Softw."},{"key":"44_CR14","doi-asserted-by":"publisher","first-page":"111349","DOI":"10.1016\/j.jss.2022.111349","volume":"190","author":"J Yuste","year":"2022","unstructured":"Yuste, J., Duarte, A., Pardo, E.G.: An efficient heuristic algorithm for software module clustering optimization. J. Syst. Softw. 190, 111349 (2022)","journal-title":"J. Syst. Softw."}],"container-title":["Lecture Notes in Computer Science","Metaheuristics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-26504-4_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T08:05:55Z","timestamp":1688198755000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-26504-4_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031265037","9783031265044"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-26504-4_44","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"23 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Metaheuristics International Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ortigia-Syracuse","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"metic2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ants-lab.it\/mic2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"72","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"67% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}